Residual noise compensation by a sequential EM algorithm for robust speech recognition in nonstationary noise
نویسندگان
چکیده
We model noise as a stationary component plus a time varying residual. The stationary part is estimated off-line and compensated using Log-Add noise compensation. The time varying residual is estimated and compensated using a sequential EM algorithm. The residual noise compensation proceeds in parallel with the recognition process. Experimental results demonstrate that the proposed algorithm improves the recognition performance not only in highly nonstationary noise but also in slow-varying noise, compared with Log-Add noise compensation alone.
منابع مشابه
Residual noise compensation for robust speech recognition in nonstationary noise
We present a model-based noise compensation algorithm for robust speech recognition in nonstationary noisy environments. The effect of noise is split into a stationary part, compensated by parallel model combination, and a time varying residual. The evolution of residual noise parameters is represented by a set of state space models. The state space models are updated by Kalman prediction and t...
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